Intelligent gathering of historical performance information

ABSTRACT

A method for intelligently gathering historical performance information for computing resources is disclosed. In one embodiment, such a method includes determining a set of computing resources for which to gather performance information. The method further designates criteria that is used to divide the computing resources into subsets. For a first subset of computing resources, the method gathers performance information for the first subset at a first frequency. For a second subset of computing resources, the method gathers performance information for the second subset at a second frequency that differs from the first frequency. Computing resources may move between the first and second subsets based on whether they satisfy or do not satisfy the criteria. A corresponding system and computer program product are also disclosed.

BACKGROUND Field of the Invention

This invention relates to systems and methods for gathering historicalperformance information for computing systems such as storage systems.

Background of the Invention

An application's performance is typically not only affected by thedesign of the application itself, but by components that the applicationuses or to which it connects. These components may include, for example,servers, network devices, application components, and storage systemsthat are utilized by the application during the course of its operation.One of the most common performance bottlenecks for an application is thestorage system to which it performs I/O. Within the storage system,there are many different resources that may affect the performance ofthe storage system, including storage drives, logical volumes, hostadapter cards, device adapter cards, cache, processors, I/O ports,storage arrays or pools, and the like. Poor performance of any of theseresources may cause the storage system to perform poorly.

For this reason, the performance of storage system resources may bemonitored to ensure that the storage system is operating in an optimalmanner and doing its part to deliver satisfactory applicationperformance. In certain cases, this may be accomplished by gathering andstoring performance information for storage system resources.Unfortunately, the number of resources in a storage system can be verylarge. For example, a storage system such as the IBM DS8000™ enterprisestorage system may host up to 64K logical volumes on its storage drives.Monitoring and storing information related to the performance of each ofthese resources can require a significant amount of storage space,processing power, and time. In some cases, the large number of resourcesmay limit the number of resources that can be monitored and/or limit thetypes or frequency of information that can be gathered from theseresources.

In view of the foregoing, systems and methods are needed to provideeffective monitoring of computing resources in storage or othercomputing systems. Ideally, such systems and methods will provideeffective monitoring and data gathering even when the number ofresources that need to be monitored is very large. Further needed aresystems and methods to limit the amount of storage space and processingpower needed to perform the monitoring and data gathering.

SUMMARY

The invention has been developed in response to the present state of theart and, in particular, in response to the problems and needs in the artthat have not yet been fully solved by currently available systems andmethods. Accordingly, embodiments of the invention have been developedto intelligently gather historical performance information for computingresources. The features and advantages of the invention will become morefully apparent from the following description and appended claims, ormay be learned by practice of the invention as set forth hereinafter.

Consistent with the foregoing, a method for intelligently gatheringhistorical performance information for computing resources is disclosed.In one embodiment, such a method includes determining a set of computingresources for which to gather performance information. The methodfurther designates criteria that is used to divide the computingresources into subsets. For a first subset of computing resources, themethod gathers performance information for the first subset at a firstfrequency. For a second subset of computing resources, the methodgathers performance information for the second subset at a secondfrequency that differs from the first frequency. Computing resources maymove between the first and second subsets based on whether they satisfyor do not satisfy the criteria. A corresponding system and computerprogram product are also disclosed and claimed herein.

BRIEF DESCRIPTION OF THE DRAWINGS

In order that the advantages of the invention will be readilyunderstood, a more particular description of the invention brieflydescribed above will be rendered by reference to specific embodimentsillustrated in the appended drawings. Understanding that these drawingsdepict only typical embodiments of the invention and are not thereforeto be considered limiting of its scope, the embodiments of the inventionwill be described and explained with additional specificity and detailthrough use of the accompanying drawings, in which:

FIG. 1 is a high-level block diagram showing one example of a networkenvironment in which systems and methods in accordance with theinvention may be implemented;

FIG. 2 is a high-level block diagram showing one example of a storagesystem, containing various computing resources, for use in the networkenvironment of FIG. 1;

FIG. 3 is a high-level block diagram showing a hardware managementconsole for gathering and storing performance information for computingresources of a storage system;

FIG. 4 is a high-level block diagram showing various samplingfrequencies and retention periods for computing resources that are beingmonitored;

FIG. 5 is a high-level block diagram showing one embodiment of anintelligent data gathering module to provide various and functions inaccordance with the invention;

FIG. 6 is a process flow diagram showing a method for turning onintelligent data gathering in accordance with the invention;

FIG. 7 is a process flow diagram showing a method for performingintelligent data gathering for two different subsets of computingresources; and

FIG. 8 is a process flow diagram showing a method for taking a snapshotof performance information in a rolling window when an event is detectedin association with a computing resource.

DETAILED DESCRIPTION

It will be readily understood that the components of the presentinvention, as generally described and illustrated in the Figures herein,could be arranged and designed in a wide variety of differentconfigurations. Thus, the following more detailed description of theembodiments of the invention, as represented in the Figures, is notintended to limit the scope of the invention, as claimed, but is merelyrepresentative of certain examples of presently contemplated embodimentsin accordance with the invention. The presently described embodimentswill be best understood by reference to the drawings, wherein like partsare designated by like numerals throughout.

The present invention may be embodied as a system, method, and/orcomputer program product. The computer program product may include acomputer readable storage medium (or media) having computer readableprogram instructions thereon for causing a processor to carry outaspects of the present invention.

The computer readable storage medium may be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages.

The computer readable program instructions may execute entirely on auser's computer, partly on a user's computer, as a stand-alone softwarepackage, partly on a user's computer and partly on a remote computer, orentirely on a remote computer or server. In the latter scenario, aremote computer may be connected to a user's computer through any typeof network, including a local area network (LAN) or a wide area network(WAN), or the connection may be made to an external computer (forexample, through the Internet using an Internet Service Provider). Insome embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, may be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus, or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

Referring to FIG. 1, one example of a network environment 100 isillustrated. The network environment 100 is presented to show oneexample of an environment where systems and methods in accordance withthe invention may be implemented. The network environment 100 ispresented only by way of example and not limitation. Indeed, the systemsand methods disclosed herein may be applicable to a wide variety ofnetwork environments, in addition to the network environment 100 shown.

As shown, the network environment 100 includes one or more computers102, 106 interconnected by a network 104. The network 104 may include,for example, a local-area-network (LAN) 104, a wide-area-network (WAN)104, the Internet 104, an intranet 104, or the like. In certainembodiments, the computers 102, 106 may include both client computers102 and server computers 106 (also referred to herein as “host systems”106). In general, the client computers 102 initiate communicationsessions, whereas the server computers 106 wait for requests from theclient computers 102. In certain embodiments, the computers 102 and/orservers 106 may connect to one or more internal or externaldirect-attached storage systems 109 (e.g., arrays or individualhard-disk drives, solid-state drives, tape drives, etc.). Thesecomputers 102, 106 and direct-attached storage systems 109 maycommunicate using protocols such as ATA, SATA, SCSI, SAS, Fibre Channel,or the like.

The network environment 100 may, in certain embodiments, include astorage network 108 behind the servers 106, such as astorage-area-network (SAN) 108 or a LAN 108 (e.g., when usingnetwork-attached storage). This network 108 may connect the servers 106to one or more storage systems, such as arrays 110 of hard-disk drivesor solid-state drives, tape libraries 112, individual hard-disk drives114 or solid-state drives 114, tape drives 116, CD-ROM libraries, or thelike. To access a storage system 110, 112, 114, 116, a host system 106may communicate over physical connections from one or more ports on thehost 106 to one or more ports on the storage system 110, 112, 114, 116.A connection may be through a switch, fabric, direct connection, or thelike. In certain embodiments, the servers 106 and storage systems 110,112, 114, 116 may communicate using a networking standard such as FibreChannel (FC).

Referring to FIG. 2, one embodiment of a storage system 110 containingan array of hard-disk drives 204 and/or solid-state drives 204 isillustrated. As shown, the storage system 110 includes a storagecontroller 200, one or more switches 202, and one or more storage drives204, such as hard disk drives 204 or solid-state drives 204 (such asflash-memory-based drives 204). The storage controller 200 may enableone or more hosts 106 (e.g., open system and/or mainframe servers 106running operating systems such z/OS, zVM, or the like) to access data inthe one or more storage drives 204.

In selected embodiments, the storage controller 200 includes one or moreservers 206. The storage controller 200 may also include host adapters208 and device adapters 210 to connect the storage controller 200 tohost devices 106 and storage drives 204, respectively. Multiple servers206 a, 206 b may provide redundancy to ensure that data is alwaysavailable to connected hosts 106. Thus, when one server 206 a fails, theother server 206 b may pick up the I/O load of the failed server 206 ato ensure that I/O is able to continue between the hosts 106 and thestorage drives 204. This process may be referred to as a “failover.”

In selected embodiments, each server 206 may include one or moreprocessors 212 and memory 214. The memory 214 may include volatilememory (e.g., RAM) as well as non-volatile memory (e.g., ROM, EPROM,EEPROM, hard disks, flash memory, etc.). The volatile and non-volatilememory may, in certain embodiments, store software modules that run onthe processor(s) 212 and are used to access data in the storage drives204. The servers 206 may host at least one instance of these softwaremodules. These software modules may manage all read and write requeststo logical volumes in the storage drives 204.

One example of a storage system 110 having an architecture similar tothat illustrated in FIG. 2 is the IBM DS8000™ enterprise storage system.The DS8000™ is a high-performance, high-capacity storage controllerproviding disk storage that is designed to support continuousoperations. Nevertheless, the apparatus and methods disclosed herein arenot limited to operation with the IBM DS8000™ enterprise storage system110, but may operate with any comparable or analogous storage system110, regardless of the manufacturer, product name, or components orcomponent names associated with the system 110. Furthermore, any storagesystem that could benefit from one or more embodiments of the inventionis deemed to fall within the scope of the invention. Thus, the IBMDS8000™ is presented only by way of example and is not intended to belimiting.

As previously mentioned, an application's performance is typicallyaffected by components that the application uses or to which itconnects. These components may include, for example, servers, networkdevices, application components, and storage systems that are utilizedby the application during the course of its operation. One of the mostcommon performance bottlenecks for an application is a storage system,such as the storage system 110 illustrated in FIG. 2. Within a storagesystem 110, there are many different computing resources that may affectthe overall performance of the storage system 110, including the storagedrives 204, logical volumes 302 (as shown in FIG. 3) carved out from thestorage drives 204, host adapters 208, device adapters 210, cache 214and memory 214 more generally, processors 212, I/O ports 216, storagearrays or pools created from the storage drives 204, and the like. Poorperformance of any of these resources may cause the overall storagesystem 110 to perform poorly.

For this reason, the performance of storage system resources may bemonitored to ensure that the storage system 110 is operating in anoptimal manner and doing its part to deliver satisfactory applicationperformance. In certain cases, this may be accomplished by gathering andstoring historical performance information for resources within thestorage system 110. Unfortunately, the number of resources in a storagesystem 110 such as that illustrated in FIG. 2 may be very large. Forexample, a storage system 110 such as the IBM DS8000™ enterprise storagesystem may host up to 64K logical volumes 302. Monitoring theperformance of each of these logical volumes 302 in addition to otherresources in the storage system 110 may require a significant amount ofstorage space, processing power, and time. In some cases, the largenumber of resources may limit the number of resources that can bemonitored and/or limit the types or frequency of information that can begathered from the resources.

Thus, systems and methods are needed to provide effective resourcemonitoring and data gathering in storage systems 110 or other computingsystems. Ideally, such systems and methods can provide effectivemonitoring and data gathering even where the number of resources (alsoreferred to herein as “computing resources”) that need to be monitoredin very large. Further needed are systems and methods to limit theamount of storage space and processing power that are needed to performsuch monitoring and data gathering.

Referring to FIG. 3, in certain embodiments, a hardware managementconsole 300 or other system 300 may be used to monitor resources of astorage system 110 or other computing system, such as a host system 106.In certain embodiments, the hardware management console 300 may beconfigured to store historical performance information associated withthe resources in a repository 302. In certain embodiments, therepository 302 is implemented on local storage (e.g., a local disk driveor solid state drive) within the hardware management console 300. Aspreviously mentioned, because the number of computing resources in astorage system 110 may be very large, the repository 302 may be limitedin its ability to store historical performance info for the computingresources. Thus, in certain embodiments, the hardware management console300 may be configured to more intelligently gather and store historicalperformance info to more efficiently utilize storage space in therepository 302.

Referring to FIG. 4, while continuing to refer generally to FIG. 3, incertain embodiments in accordance with the invention, the hardwaremanagement console 300 may periodically sample performance information(e.g., latency, bandwidth, number of I/O operations, number of I/Ooperations per unit of time, etc.) from the computing resources andstore this information in the repository 302. Because a computing systemsuch as the storage system 110 may include many computing resources andthe storage space in the repository 302 may be finite, the hardwaremanagement console 300 may prioritize which computing resources willhave their information gathered, and the amount of information storedfor each computing resource. In certain embodiments, this prioritizationmay be designated by a user, or the prioritization may be set ordetermined by algorithm as will be explained in more detail hereafter.

FIG. 4 shows an example of how sampling frequencies may be adjustedbased on priority. As shown in FIG. 4, computing resources that aredeemed of greater importance or priority may be queried for performanceinformation at a first sampling frequency (e.g., every minute), whilecomputing resources that are deemed of lesser importance or priority maybe queried for performance information at a second sampling frequency(e.g., every five minutes). In certain embodiments, this performanceinformation may be retained in the repository 302 in accordance with adesignated retention policy. For example, performance information forcomputing resources of greater importance or priority may be may bemaintained for a first retention period, while performance informationfor computing resources of lesser importance or priority may be may bemaintained for a second retention period. In certain embodiments, thefirst and second retention periods are the same (e.g., one week) whilein other embodiments the first and second retention periods aredifferent. For example, the first retention period may be greater thanthe second retention period to reflect the greater importance attributedto the associated computing resources.

As further shown in FIG. 4, in certain embodiments, performanceinformation of each computing resource may be sampled and stored over ashort window (e.g., five minutes) at a relatively high frequency (e.g.,every minute). This is referred to herein as a “rolling window” sincesampled performance information is deleted after five minutes hastranspired from the time it is sampled. In certain embodiments, this mayoccur for all computing resources regardless of their designatedpriority or importance. If an event, such as error, is detected in acomputing resource, a snapshot of this rolling window may be taken andsaved off to more persistent and longer term storage. This may assist inanalyzing the computing resource during the window when the eventoccurred. The higher sampling frequency may provide more performanceinformation with finer granularity to aid in the analysis. Because ofthe higher sampling frequency, the retention period may be kept short toreduce the amount of storage space that is consumed by data sampledduring the rolling window.

Referring to FIG. 5, to provide the functionality described above inassociation with FIGS. 3 and 4, an intelligent data gathering module 500maybe provided in the hardware management console 300. This intelligentdata gathering module 500 may provide a more intelligent and efficientway to store performance information for computing resources,particularly large numbers of computing resources. The intelligent datagathering module 500 may be implemented in software, hardware, firmware,or a combination thereof and is not necessarily limited toimplementation within a hardware management console 300.

As shown, the intelligent data gathering module 500 includes varioussub-modules 502-526 to provide various features and functions. Thesesub-modules are presented by way of example and not limitation. More orfewer sub-modules may be provided in different embodiments. For example,the functionality of some sub-modules may be combined into a single orsmaller number of sub-modules, or the functionality of a singlesub-module may be distributed across several sub-modules.

As shown, the intelligent data gathering module 500 may include one ormore of a computing resource designation module 502, threshold module504, criteria module 506, determination module 508, frequency module510, retention module 512, sampling module 514, calculation module 516,storage module 518, deletion module 520, rolling window module 522,event detection module 524, and save module 526.

The computing resource designation module 502 may be configured todesignate which computing resources to monitor. In certain embodiments,a user may select the computing resources to monitor, or the computingresources may be selected by algorithm. In certain embodiments, thecomputing resource designation module 502 may designate all computingresources in a particular system, all computing resources of certaintypes (e.g., logical volumes 302, host adapters 208, device adapters210, etc.), or individual computing resources.

The threshold module 504 may determine whether all computing resourcescan be monitored at full rate without overwhelming or exceeding thecapacity of the repository 302. For example, if the number of computingresources is small enough, the repository 302 may be large enough tostore performance information for the computing resources withoutreducing the amount of information stored. However, if the number ofcomputing resources reaches a threshold, the threshold module 504 maydetermine that more intelligent monitoring and data storage is needed.This may trigger the intelligent data gathering module 500 to use a moreefficient monitoring and storing technique, such as the techniquediscussed in association with FIG. 4. For example, more importantcomputing resources may have performance information sampled at a higherfrequency whereas less important computing resources may haveperformance information sampled at a lower frequency to reduce theamount of data stored in the repository 302.

The criteria module 506 may establish criteria for deciding whether acomputing resource is sampled at the higher or lower rate (i.e.,determines whether the computing resource belongs to a first subset thatis sampled at a higher rate, or to a second subset that is sampled at alower rate). For example, in certain embodiments, the top ten percent ofcomputing resources in terms of I/O processing may be sampled at thehigher rate whereas all other computing resources may be sampled at thelower rate. In another example, the most error-prone computing resourcesmay be sampled at the higher rate whereas the least error-pronecomputing resources may be sampled at the lower rate. This will storemore comprehensive performance information for more error-pronecomputing resources. Other criteria are possible and within the scope ofthe invention.

The determination module 508 may determine whether a computing resourcemeets the criteria established by the criteria module 506. Depending onwhether a computing resource satisfies or does not satisfy the criteria,the frequency module 510 may determine a frequency with which to samplethe computing resource, and the retention module 512 may determine theretention period to retain performance information associated with thecomputing resource. For example, performance information for moreimportant computing resources may be sampled at a higher frequency andhave a longer retention time whereas performance information for lessimportant computing resources may be sampled at a lower frequency andhave a shorter retention time.

Once the sampling frequency is determined for a computing resource, thesampling module 514 may sample performance information of the computingresource at the designated sampling frequency. In certain embodiments,the calculation module 516 may calculate different statistics (e.g.,averages, rates, etc.) based on the sampled performance information. Forexample, if the sampling module 514 samples the number of I/Os processedby a computing resource at certain intervals, the calculation module 516may calculate the I/Os per second (IOPS) by dividing the number of I/Osby the time between samples. Thus, in certain embodiments, thecalculation module 516 may derive certain statistics or metrics from theperformance information gathered by the sampling module 514.

Once desired performance information and/or statistics are gathered, thestorage module 518 may store this information in the repository 302.This information may be retained in the repository 302 for theestablished retention period. Once the retention period has expired, thedeletion module 520 may delete the information from the repository 302to free up storage space and to accommodate future performanceinformation and/or statistics.

The rolling window module 522 may be configured to implement the rollingwindow previously described in association with FIG. 4. As previouslyexplained, performance information of computing resources may be sampledat a higher frequency during this rolling window, but deleted morerapidly than normal from the repository 302 to reduce utilization ofstorage space. Similarly, the event detection module 524 may beconfigured to detect an event, such as an error or condition, that auser may want to analyze more closely for a particular computingresource. The more frequent sampling may enable a user to take a closerlook at conditions surrounding the event. When an event is detected, thesave module 526 may take a snapshot of performance information containedin the rolling window and save it to more persistent and longer-termstorage. The snapshot may include information gathered some time (e.g.,five minutes) before the event as well as some time (e.g., five minutes)after the event.

Referring to FIG. 6, one embodiment of a method 600 for turning onintelligent data gathering in accordance with the invention isillustrated. As shown, the method 600 initially determines 602 whatcomputing resources are to be monitored. The method 600 then determines604 whether there are too many resources to be monitored at full ratewithout data reduction. If there are not too many resources, the method600 uses 612 conventional data gathering and storing techniques togather and store performance information for the computing resources.

If, on the other hand, there are too many resources, the method 600designates 606 criteria for determining whether a computing resource issampled at a higher or lower rate. The criteria may be used to dividethe computing resources into different subsets of computing resourcesthat are sampled differently. The method 600 determines 608 a samplingfrequency and retention policy for computing resources in each of thesubsets. Once the criteria, sampling frequency, and retention policy aredetermined, the method 600 uses 610 the intelligent data gathering andstoring techniques to gather and store performance information for thecomputing resources.

Referring to FIG. 7, one embodiment of a method 700 for performingintelligent data gathering for two different subsets of computingresources is illustrated. More subsets are possible in otherembodiments. As shown, once computing resources are selected formonitoring, the method 700 determines 702 whether each computingresource satisfies the criteria established 606 in the method 600 ofFIG. 6. If a computing resource satisfies 702 the criteria, the method700 assigns 704 a the computing resource to a first subset. The method700 then samples 706 a the performance information of the computingresource at the frequency associated with the first subset. If needed,the method 700 calculates 708 a statistics based on the performanceinformation gathered at step 706 a. The method 700 then stores 710 a theinformation/statistics in the repository 302. The method 700 furtherdeletes 712 a the information/statistics from the repository 302 after aretention period associated with the second subset has expired.

If a computing resource does not satisfy 702 the criteria, the method700 assigns 704 b the computing resource to the second subset. Themethod 700 then samples 706 b performance information of the computingresource at the frequency associated with the second subset. If needed,the method 700 calculates 708 b statistics based on the performanceinformation gathered at step 706 b. The method 700 then stores 710 b theinformation/statistics in the repository 302. The method 700 deletes 712b the information/statistics from the repository 302 after a retentionperiod associated with the first subset has expired.

Referring to FIG. 8, one embodiment of a method 800 is illustrated forsaving windows of performance information when an event is detected. Asshown, the method 800 establishes 802 a rolling window for samplingperformance information from computing resources. The method 800 furtherestablishes 804 a retention policy in association with the rollingwindow. When an event is detected 806, the method 800 takes 808 asnapshot of the performance information in the rolling window and saves808 it to more persistent and longer-term storage. This snapshot isdeleted 810 after the retention policy established at step 804 hasexpired.

The flowcharts and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowcharts or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the Figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. Other implementationsmay not require all of the disclosed steps to achieve the desiredfunctionality. It will also be noted that each block of the blockdiagrams and/or flowchart illustrations, and combinations of blocks inthe block diagrams and/or flowchart illustrations, may be implemented byspecial purpose hardware-based systems that perform the specifiedfunctions or acts, or combinations of special purpose hardware andcomputer instructions.

1. A method for intelligently gathering historical performanceinformation for computing resources, the method comprising: determininga set of computing resources for which to gather performanceinformation; for a first subset of computing resources from the set thatsatisfy a criteria, gathering first performance information for thefirst subset at a first frequency; and for a second subset of computingresources from the set that do not satisfy the criteria, gatheringsecond performance information for the second subset at a secondfrequency, wherein the second frequency is different from the firstfrequency.
 2. The method of claim 1, further comprising moving computingresources between the first and second subsets based on whether thecomputing resources satisfy the criteria.
 3. The method of claim 1,further comprising storing the first performance information for a firstperiod of time prior to deletion.
 4. The method of claim 3, furthercomprising storing the second performance information for a secondperiod of time prior to deletion.
 5. The method of claim 4, wherein thefirst period of time is different from the second period of time.
 6. Themethod of claim 4, wherein the first period of time is the same as thesecond period of time.
 7. The method of claim 1, wherein the computingresources include at least one of arrays of storage drives, individualstorage drives, a storage system as a whole, storage pools, I/O ports,host adapters, device adapters, cache, and processor nodes.
 8. Acomputer program product for intelligently gathering historicalperformance information for computing resources, the computer programproduct comprising a computer-readable storage medium havingcomputer-usable program code embodied therein, the computer-usableprogram code configured to perform the following when executed by atleast one processor: determine a set of computing resources for which togather performance information; for a first subset of computingresources from the set that satisfy a criteria, gather first performanceinformation for the first subset at a first frequency; and for a secondsubset of computing resources from the set that do not satisfy thecriteria, gather second performance information for the second subset ata second frequency, wherein the second frequency is different from thefirst frequency.
 9. The computer program product of claim 8, wherein thecomputer-usable program code is further configured to move computingresources between the first and second subsets based on whether thecomputing resources satisfy the criteria.
 10. The computer programproduct of claim 8, wherein the computer-usable program code is furtherconfigured to store the first performance information for a first periodof time prior to deletion.
 11. The computer program product of claim 10,wherein the computer-usable program code is further configured to storethe second performance information for a second period of time prior todeletion.
 12. The computer program product of claim 11, wherein thefirst period of time is different from the second period of time. 13.The computer program product of claim 11, wherein the first period oftime is the same as the second period of time.
 14. The computer programproduct of claim 8, wherein the computing resources include at least oneof arrays of storage drives, individual storage drives, a storage systemas a whole, storage pools, I/O ports, host adapters, device adapters,cache, and processor nodes.
 15. A system for intelligently gatheringhistorical performance information for computing resources, the systemcomprising: at least one processor; at least one memory device operablycoupled to the at least one processor and storing instructions forexecution on the at least one processor, the instructions causing the atleast one processor to: determine a set of computing resources for whichto gather performance information; for a first subset of computingresources from the set that satisfy a criteria, gather first performanceinformation for the first subset at a first frequency; and for a secondsubset of computing resources from the set that do not satisfy thecriteria, gather second performance information for the second subset ata second frequency, wherein the second frequency is different from thefirst frequency.
 16. The system of claim 15, wherein the instructionsfurther cause the at least one processor to move computing resourcesbetween the first and second subsets based on whether the computingresources satisfy the criteria.
 17. The system of claim 15, wherein theinstructions further cause the at least one processor to store the firstperformance information for a first period of time prior to deletion.18. The system of claim 17, wherein the instructions further cause theat least one processor to store the second performance information for asecond period of time prior to deletion.
 19. The system of claim 18,wherein the first period of time is different from the second period oftime.
 20. The system of claim 18, wherein the first period of time isthe same as the second period of time.